code: def test_cosine_similarity_chunk():
      X = np.random.rand(333, 100)
      start_idx = 10
      end_idx = 100
  
      input_tuple = (X, (start_idx, end_idx))
  
      result = cosine_similarity_chunk(input_tuple)
  
      np.testing.assert_array_almost_equal(
          result,
          cosine_similarity(X[start_idx:end_idx, :], X).astype(
              "float16"
          ),
      )
  
file_path: imagededup/tests/test_retrieval.py
imports: import sys
  import pytest
  import numpy
  from sklearn.metrics.pairwise import cosine_similarity
  from imagededup.handlers.search.retrieval import HashEval, cosine_similarity_chunk, get_cosine_similarity
  from imagededup.methods.hashing import Hashing
label_desc: Use image node_id 1 for calling a global function with example usage: test_cosine_similarity_chunk() without return types